以類神經網路分析影響製程創新成功之因素

The Study of Neural Network Analysis Affect Successful Factors of Process Innovation

10.6338/JDA.201202_7(1).0005

徐怡(Yi Hsu)；吳翰勳(Han-Hsun Wu)

製程創新 ； 專利技術 ； 產品創新 ； 資訊來源 ； 創新支出 ； Process innovation ； Patented technology ； Product innovation ； Sources information ； Innovation expenditure

Journal of Data Analysis

7卷1期（2012 / 02 / 01）

75 - 105

繁體中文

近年來，全球產業正面臨全球化與物料高漲之情形，導致產業環境日趨嚴苛；製程創新技術能夠有效的幫助企業降低成本與提升生產效率。本研究針對台灣5021家製造業做為研究對象，並且採用類神經多層感知模型（MLP）分析台灣製造業的營運模式、政府補助、資訊來源、創新支出、產品創新、專利技術以及組織創新對製程創新成功之因素。結果發現，營運模式、政府補助、資訊來源（包括市場來源、公眾來源、其他來源）以及創新支出對於製程創新有顯著正影響；資訊來源（包含內部來源）、專利技術以及組織創新對於製程創新無顯著正向影響；產品創新對於製程創新無顯著負向影響。

In recent years, the global industry is facing the situation of globalization and rising materials' price, leading industrial environment increasingly harsh; process innovation can effectively help companies reduce costs and improve productivity. In this study, we conducted a research of 5021 manufacturing firms in Taiwan and applied neural multi-layer perception model (MLP) for analysis the effects of Taiwanese manufacturing firm's business model, government grants, information sources, innovation expenditure, product innovations, patented technology and organizational innovation on process innovation. The results indicated that the mode of operation, government grants, information sources (including market sources, public sources, other sources), and innovation expenditures had significantly positive correlation to process innovation; information sources (including internal sources), patented technology, and organizational innovation had insignificantly positive correlation to process innovation; product innovation had insignificantly negative correlation to the innovation process.

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